In the complex society that we are living in, there are numerous occasions where individuals have to authenticate themselves by means other than personal recognition. Until recently, a common approach to this has been the issuance of personal identification cards which range in complexity depending on the purpose for which they are to be used. For situations that are deemed only of secondary importance, the cards may merely contain the individual's name, signature and an identification number. Here, the presentation of the card will be proof enough of the user's identity if the card signature matches that of the user's as taken at the time of use. For situations that require a more positive identification, such cards are also provided with the individual's photograph, as in the case for driver's licenses and passports.
Unfortunately, these identification instruments have become the common victims of illegal falsification and duplication. The rampant credit card fraud of recent years has certainly accentuated the inadequacy of using such personal instruments to authenticate oneself in many instances. To this end when bank-issued ATM cards were finally accepted and used by the American public in large numbers in the middle 1980's, a new identification means was introduced in the form of what is now called a PIN number, or Personal Identification Number, which typically takes the form of an easily-memorisable 4-digit decimal number.
Even though there exist superior ways and methods for use in identifying or authenticating an individual, particularly those that use one's natural body codes such as faces, fingerprints, retina patterns, irises and voice prints, they have only been deployed to date in highly special circumstances where the absolute security of one's identity warrants the additional complexity. Indeed the use of fingerprints to identify unique individuals has been around for well over a hundred years. Either “rolled” fingerprint or “flatly placed” fingerprint inked impressions are commonly used and the identification can be classified as “passive” because the individual is not required to perform any finger motions during the subsequent process of identification. As is well-known, in collecting the so-called “rolled” fingerprint impressions, an individual's inked thumb or other fingers is rotated from one side of the nail to the other so that the entire pattern area can be printed on paper. Characteristic features or patterns of fingerprints such as “arches”, “loops” and “whorls” (referred to as keys) are routinely employed by fingerprint-identifying technicians to define fingerprint patterns for easier comparison and identification of them. The so-called Henry classification system is often used to determine if two prints are the same even though this system requires a skilled expert to compare the individual characteristics of the prints.
The classical approach of using fingerprints to identify individuals, albeit among one of the best known to date, is nevertheless rather complex and may require elaborate optical instruments such as high-power microscopes for detailed fingerprint pattern examinations. Collection of inked fingerprint impressions can be rather messy and also takes operator skill and a finite amount of time in order to do an adequate job. As mentioned above, identification of fingerprints belonging to unique individuals using comparison methods requires trained experts or experienced technicians. Furthermore identification of individuals via fingerprint matching is not really an exact science and is by no means 100% objective or accurate. Added to all these is the fact that an individual's fingerprints are not safe or fully protected from fraudulent use because most people frequently and inadvertently leave behind fingerprints while performing their daily routines. These fingerprints can be willfully recovered for illegal use as falsified personal identifications.
Not surprisingly, not all people feel comfortable in submitting their fingerprints for their personal identification such as credit cards, employee entrance cards in workplaces etc. except for very serious matters such as extreme security check for sensitive federal appointments or for crime solving. One important reason behind this is the fact that there is an undesirable stigma of “criminal nature” associated with the use of fingerprints as a method of identification. Replacing specially trained and experienced fingerprint-identifying technicians requires the use of very complicated detection machines equipped with complex processing algorithms. These equipment are therefore necessarily expensive. Still, in an effort to try to thwart the rampant credit card fraud, proposals have been advanced over the past several years to utilize one's fingerprint as a more secure way of authenticating credit card holders. The use of fingerprints along with the use of the so-called “smart cards”, namely cards that encapsulate a secure smart integrated circuit (IC) chip in the plastic in lieu of the fraud-prone magnetic stripe for storing sensitive and personal financial data, would surely eliminate once and for all the credit card fraud problem existing today. The development of the so-called biometric smart card using fingerprint template identification has been on-going for a number of years but unfortunately is still far from being a reality because of credit card size and the cost constraints of this method, in addition to having to overcome very difficult technical challenges.
However, the technical obstacles that have been encountered to date in the implementation of the full-blown fingerprint identification approach in the biometric smart card should not be the determining factor in deciding whether or not this venerable identification method should be deployed in the future. Furthermore, the deployment of the retina pattern, iris and the voice print as better and alternate ways to identify individuals will likely encounter the same constraint problems in size, cost and technical challenge without the benefit of a head start like the use of fingerprints. Today the rampant credit card fraud problem has not gone away. As a matter of fact, the problem grows worse and more serious everyday that passes. Thus there presently exist ample reasons why a new and better methodology is needed in order to exploit the use of fingerprints as a secure way of authenticating individuals, especially in circumstances of primary importance like access to restricted area or restricted information, or authorization of credit cards, without the existing encumbrances of using fingerprints for identification as discussed earlier above.
Ample prior art can be found in fingerprint detection apparatus and methodology of using fingerprints for personal authentication and identification. A list of earlier issued U.S. patents relating to the prior art has been presented in U.S. application Ser. No. 10/074,011 filed Feb. 14, 2002 for “Authentication Method Utilizing a Sequence of Linear Partial Fingerprint Signatures Selected by a Personal Code”, of which the present application is a second generation continuation-in-part. Additional prior art dealing with two-dimensional fingerprint images, their acquisition methodology and apparatus, and their classification, interpretation and comparison are presented as follows.
In U.S. Pat. No. 5,933,515 issued to Pu et al. in 1999, an identification system using biometric information of human body parts and a secret sequence code was advanced. In particular, biometric information of human body parts is used to form the secret sequence code. Specifically, a combination entry device recognizes user's fingerprints which are entered as a sequence. The fingerprints must be entered in the proper sequence in order to be recognized by the system. Although in principle this invention has a lot of merit and was among the first to introduce the concept of giving an individual a choice in how to use his biometric information as a way of his identification, only the use of different complete fingerprints to form the biometric sequence was taught. Thus the implementation of this teaching is in reality extremely cumbersome and time consuming and it is certainly not amenable to simple and low-cost realization in order to be universally practical.
In U.S. Pat. No. 5,982,913 issued to Brumbley et al. in 1999, a method of fingerprint verification was advanced that includes the steps of capturing a complete fingerprint of a number of enrollees; capturing a portion of a claimant's fingerprint, where the portion is less than an entire fingerprint; dividing the portion of the claimant's fingerprint into a number of segments; comparing each of the segments against the fingerprint of the enrollee the claimant claims to be; generating a correlation score for each of the segments; calculating a distance error for the segments; combining the distance errors into an average distance error; generating a verification vector based on each of the correlation scores for each of the segments and the distance error; establishing a threshold vector; and comparing the verification vector against the threshold vector in order to determine whether or not the claimant is the enrollee the claimant claims to be. It is clear that the primary objective of the inventors is to simplify the fingerprint verification process by devising means for comparing portions of a complete fingerprint with a complete reference fingerprint. The means used to achieve this objective are still overly complicated and are not easily amenable to simple and low-cost implementation.
In U.S. Pat. No. 6,226,391 issued to Dydyk et al. in 2001, a method and apparatus for automatically placing a first unknown image, such as an unknown fingerprint image, into one of a plurality of categories. The invention includes storing in a library a plurality of value series, each of which series is derived from the frequency representation of an image category. The categorization process and apparatus takes the frequency image of a first unknown pattern to create a first frequency image the frequency image plane of the first (unknown) frequency image is divided into a plurality of frequency image plane regions. Each of the frequency image plane regions may be an angular segment radiating from the origin of the frequency image plane. A region value is assigned to each of the frequency image plane regions based on the total energy in the frequency image in that region. The region values for the first frequency image are combined to generate a first series of region values. The first series of region values is compared in a comparator with each of the stored value series. The comparator preferably performs a correlation function on the pattern or series of the regional values using the one dimensional frequency transform of the spatial representation of the pattern or series of regional values.
Although this invention discloses the concept of fingerprint classification using spatial frequency representation, correlation functions and one-dimensional frequency transform, the apparatus advanced to generate the frequency image of an unknown pattern in order to utilize such a classification methodology is rather complex and is certainly not amenable to simple and low-cost implementation.
In U.S. Pat. No. 6,241,288 issued to Bergenek et al. in 2001, a novel fingerprint identification/verification system was disclosed. This system uses bitmaps of a stored fingerprint to correlate with a bit map of an input fingerprint, wherein an accurate reference point is located. This is followed by the selection of several two-dimensional areas in the vicinity of the reference point of the input image of the fingerprint. These areas are then correlated with stored fingerprint recognition information to determine if the input fingerprint image and the stored fingerprint recognition information are sufficiently similar to identify/verify the input fingerprint. It can be seen from this brief summary of the patent, the teaching of this invention is very complex and unlikely to be able to be implemented simply and in a low-cost manner.
Additional teachings of fingerprint identification systems and methods of related interest, particularly in the use of Fast Fourier Transform techniques for 2-dimensional fingerprint image analysis may be found in other U.S. Patents, including—U.S. Pat. No. 5,910,999 issued to Mukohzaka in 1999; U.S. Pat. No. 5,915,034 issued to Nakajima et al. in 1999; U.S. Pat. No. 5,999,637 issued to Toyoda et al. in 1999; U.S. Pat. No. 6,024,287 issued to Takai et al. in 2000; U.S. Pat. No. 6,075,876 issued to Draganoff in 2000; U.S. Pat. No. 6,094,499 issued to Nakajima et al. in 2000; U.S. Pat. No. 6,341,028 issued to Bahuguna et al. in 2002; and US 2002/0018585 A1 issued to Kim in 2002. Beyond the Fourier Transform prior art of interest, other prior U.S. patents pertaining to the proximity sensing aspect of the present invention are as follows.
U.S. Pat. No. 4,784,484 to Jensen discloses methods and apparatus for optically scanning fingerprints wherein a finger is moved over a stationary optical line scanner and a measuring circuit produces two times derived from a pair of wires which are beneath the moving finger path. The scanning line may be placed between two of the measuring wires.
U.S. Pat. No. 6,759,804 to Setlak et al. discloses using a finger pressure sensor to control power application to active fingerprint sensing circuitry. Also, U.S. Pat. No. 6,360,004 to Akizuki discloses the use of a touch pad to detect the position of finger contact, while U.S. Pat. No. 5,635,723 to Fujieda et al. discloses the use of force responsive springs to initiate fingerprint sensing circuitry.
There is hardly any doubt that the prior art summarized above and those presented in the aforementioned U.S. application Ser. No. 10/074,011 have made significant progress towards simplifying the overall mechanics for the acquisition, classification and comparison of fingerprints. They have also removed in some cases the subjectivity and ambiguity in the employment of the well-known Henry classification system to determine if two prints are the same. However, the conventional thinking of using the entirety or even portions of one's complete fingerprint on a comparison basis with stored counterparts to authenticate oneself is still today far too complex a task to accomplish simply and economically, despite the availability of clever correlation methods and high-power mathematical tools.
The approach taken by the aforementioned U.S. applications and the present continuation-in-part represent major departures from such thinking. Certain specific and well-defined partial fingerprints (e.g. linear or straight line segments) belonging to an individual are now looked upon as his biometric signatures and he has a choice of using linear signatures in a self-chosen sequence for his unique authentication. Unlike one's written signature in the past which was used for his identification but suffered from frequent illegal falsification and duplication, today one's written signature can be replaced by a so-called Personal Choice Biometric Signature (PCBS) or sequential linear signatures by choice which can neither be duplicated nor falsified for fraud. The reason for advancing this new kind of thinking is that comparing an individual's entire fingerprint against one's stored complete fingerprint is not cost effective in low-cost applications including smart card systems primarily because of the size and expense of the scanner required to capture an entire fingerprint and partly because of the amount of memory required to store and process one's entire fingerprint.